Save session activity, rebuild rolling PROGRESS.md, and compact stale working blocks in .claude/STATE.md.

MITAuto-check passed

Install Checkpointing

skills CLI
$ npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill checkpointing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install DeL-TaiseiOzaki/claude-code-orchestra checkpointing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/DeL-TaiseiOzaki/claude-code-orchestra.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/checkpointing .claude/skills/checkpointing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
checkpointing
GitHub stars
199
Token cost
~1.8k tokens
SKILL.md length
797 words
Files
4 (incl. references)
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Save session activity, rebuild rolling PROGRESS.md, and compact stale working blocks in .claude/STATE.md.

  • Works in 8 steps: Determine the time window from the… → Gather the user requests and decisions… → Write a Japanese five-part summary… → …
  • SKILL.md covers Owned Paths, Full Checkpoint, Finding a Past Checkpoint and Compact Phase, plus 1 more section
  • Runs Python scripts from its folder; calls python3

What it does

Checkpointing is an agent skill from DeL-TaiseiOzaki/claude-code-orchestra. Save session activity, rebuild rolling PROGRESS.md, and compact stale working blocks in .claude/STATE.md.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `checkpoint.py`, `references/formats.md` and `refresh_guard.py`).

The licence is MIT.

Example prompts

  • “/checkpointing”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Determine the time window from the newest checkpoint, or use all available
  2. Gather the user requests and decisions from the current conversation, git
  3. Write a Japanese five-part summary containing
  4. Save the summary to .claude/logs/pending-summary.md, then preview
  5. Review the four previews, then write for real
  6. Confirm the shared-state invariant mechanically rather than by reading
  7. Review whether durable architecture decisions belong in
  8. Run the Compact Phase below.

What it can do on your machine

Read from SKILL.md and the folder at commit ef0d8f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Checkpointing loads about 1.8k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 30 tokens; SKILL.md has 797 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from DeL-TaiseiOzaki/claude-code-orchestra at commit ef0d8f8, republished under its MIT licence (© DeL-TaiseiOzaki). 797 words, ~1,839 tokens.

Download SKILL.mdSave it as .claude/skills/checkpointing/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
checkpointing
description
Save session activity, rebuild rolling PROGRESS.md, and compact stale working blocks in .claude/STATE.md.
metadata.short-description
Full session checkpoint and shared-state compaction

Checkpointing

Capture durable session context without growing the always-loaded root AGENTS.md. Canonical state and artifacts live under .claude/.

Owned Paths

  • .claude/checkpoints/: full timestamped checkpoints; never deleted by the compact phase.
  • .claude/checkpoints/INDEX.md: generated catalog of every checkpoint.
  • PROGRESS.md: latest five checkpoint summaries.
  • .claude/STATE.md: one Progress Tracker link and current working blocks.
  • .claude/logs/: drafts, previews, work logs, and CLI activity.
  • .claude/docs/research/: research notes; inactive notes may be archived only after user approval.

Both scripts write nothing without --apply. Every default run produces preview files under .claude/logs/ and leaves PROGRESS.md and .claude/STATE.md untouched.

Full Checkpoint

  1. Determine the time window from the newest checkpoint, or use all available history when none exists.

  2. Gather the user requests and decisions from the current conversation, git changes, CLI logs, team work logs, and relevant design changes.

  3. Write a Japanese five-part summary containing: 何をしたのか, どういうやり取りをユーザーと行ったのか, どうやったのか, 途中でどういう課題が起こったのか, and 将来のアクション. This is the irreducible judgment in the skill and is never generated: a missing, empty, stale, or incomplete summary aborts the run with exit 2.

  4. Save the summary to .claude/logs/pending-summary.md, then preview:

    bash
    python3 .claude/skills/checkpointing/checkpoint.py \
      --summary-file .claude/logs/pending-summary.md

    Exit 0 reports result: preview and four preview files (checkpoint-preview-*, index-preview-*, progress-preview-*, state-preview-* under .claude/logs/). Exit 1 is a bad --since / --now; exit 2 is a summary or shared-state contract violation; exit 3 is a timestamp collision, a concurrent modification, or a write failure.

    Add --label <slug> when the session's commit messages would not name it well; the label becomes the checkpoint's slug in the frontmatter and the index.

  5. Review the four previews, then write for real:

    bash
    python3 .claude/skills/checkpointing/checkpoint.py \
      --summary-file .claude/logs/pending-summary.md \
      --apply --consume-summary --json

    --consume-summary deletes the draft on success, so the next session cannot silently embed this session's summary. --json emits the single payload {ok, result, checkpoint_path, prompt_path, index_path, slug, tags, progress_path, progress_entries, state_path, state_updated, summary_validated, summary_consumed, commits, files_changed, cli_consultations, agent_teams, work_logs, collector_errors, skipped_records, warnings, artifacts}; without it the same facts are printed as prose. Quote collector_errors and warnings verbatim when reporting — a failed collector is not an empty session.

  6. Confirm the shared-state invariant mechanically rather than by reading:

    bash
    python3 .claude/skills/checkpointing/refresh_guard.py --mode check

    Exit 0 means exactly one # Agent State and one ## Progress Tracker heading; exit 2 means the structure is invalid.

  7. Review whether durable architecture decisions belong in .claude/docs/DESIGN.md; use /design-tracker when warranted.

  8. Run the Compact Phase below.

Finding a Past Checkpoint

Three layers make retrieval cheap, so a past session is found without reading the directory file by file:

  1. .claude/checkpoints/INDEX.md — one table, newest first, with the branch, tags, counts, and headline for every checkpoint. Read this first and scan the tags and summary columns.
  2. YAML frontmatter — each checkpoint opens with id, timestamp, branch, slug, summary, tags, and the session counts. Reading the first ~14 lines settles relevance without parsing the document.
  3. PROGRESS.md — the five most recent summaries in full, for the common case of "what happened lately".

INDEX.md is regenerated from the checkpoints' frontmatter on every --apply, so a deleted or hand-edited checkpoint is reflected on the next run rather than advertised forever. Checkpoint filenames stay YYYY-MM-DD-HHMMSS.md: the slug lives in the metadata, not the path, so PROGRESS.md links and collect_repo_state.py keep working. Do not hand-edit INDEX.md.

Show full SKILL.md (309 more words)Show less

Compact Phase

The compact phase keeps only the newest ## Current Project, ## Current Feature, and ## Current Bug Fix block of each category. Every other section is preserved verbatim in document order — ## Main Agent, ## Repository Identity, ## Progress Tracker, and any manual notes, which .claude/rules/agent-state.md explicitly sanctions. A section that would still be lost is reported in sections_dropped and aborts the run with exit 2.

  1. Inspect the state, the compaction preview, and the suggested archive moves:

    bash
    python3 .claude/skills/checkpointing/refresh_guard.py --mode plan

    Reports blocks_pruned, sections_preserved, sections_dropped, research_notes, and move_plan. move_plan entries carry suggested: true: they come from a stem-mention heuristic and are never a decision.

  2. Write the candidate state to a draft:

    bash
    python3 .claude/skills/checkpointing/refresh_guard.py --mode compose
  3. Review .claude/logs/composed-state.md and the reported move plan.

  4. Ask for approval before replacing .claude/STATE.md or moving research notes. Never delete checkpoint files or regenerate PROGRESS.md here.

  5. After approval, apply the compaction with the script — never by hand:

    bash
    python3 .claude/skills/checkpointing/refresh_guard.py --mode apply
    python3 .claude/skills/checkpointing/refresh_guard.py --mode apply --apply

    The first call previews to .claude/logs/state-compaction-preview-*.md and reports state_hash_before. The second writes atomically, refuses if .claude/STATE.md changed since it was read, and validates the composed bytes before replacing. Pass --expect-hash <state_hash_before> to pin the exact revision that was approved.

  6. Confirm the compaction landed:

    bash
    python3 .claude/skills/checkpointing/refresh_guard.py --mode verify

    verify compares the on-disk state against a freshly composed candidate and reports compaction_applied. Exit 2 means redundant work blocks remain.

Safety Gates

  • Root AGENTS.md is never modified.
  • INDEX.md is generated, never hand-maintained; it is not a checkpoint and is never listed in PROGRESS.md.
  • State structure must contain exactly one # Agent State heading and one ## Progress Tracker heading.
  • Archive destinations use .claude/docs/research/archive/; append when a destination already exists.
  • All destructive moves require an explicit preview and user approval.
  • Report the checkpoint path, state blocks pruned, sections preserved, research notes archived, validation result, and remaining risks, per .claude/rules/language.md.

© DeL-TaiseiOzaki, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in .claude/skills/checkpointing of DeL-TaiseiOzaki/claude-code-orchestra.

  • SKILL.md
  • checkpoint.py
  • references/formats.md
  • refresh_guard.py

Open the folder on GitHubat commit ef0d8f8

Compare with similar skills

Checkpointing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Checkpointing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Checkpointing this skillDeL-TaiseiOzaki/claude-code-orchestra199—~1.8kAutomated safety check: PassMIT
Strategic Compactaffaan-m/ECC277k1 repos~2.1kAutomated safety check: PassMIT
Progressive Jpegthedaviddias/Front-End-Checklist74k—~426Automated safety check: PassMIT
Rebuilding Flutter Toolflutter/flutter180k—~167Automated safety check: PassBSD-3-Clause
Modeling Activation MetricsPostHog/posthog40k—~1.4kAutomated safety check: PassCustom licence
Strategic Compactaffaan-m/ECC277k2 repos~434Automated safety check: PassMIT

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Questions about Checkpointing

What does Checkpointing do?

Save session activity, rebuild rolling PROGRESS.md, and compact stale working blocks in .claude/STATE.md. Checkpointing is an agent skill from DeL-TaiseiOzaki/claude-code-orchestra.md.

How do I install Checkpointing in Claude Code?

Run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill checkpointing -a claude-code`. Or copy the skill folder (.claude/skills/checkpointing in DeL-TaiseiOzaki/claude-code-orchestra) into .claude/skills/checkpointing in your project. Claude Code loads it when a task matches its description.

How do I install Checkpointing in Codex?

Run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill checkpointing -a codex`. Or copy the skill folder (.claude/skills/checkpointing in DeL-TaiseiOzaki/claude-code-orchestra) into .agents/skills/checkpointing in your project. Codex loads it when a task matches its description.

Can I use Checkpointing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DeL-TaiseiOzaki/claude-code-orchestra --skill checkpointing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/checkpointing, .gemini/skills/checkpointing, .github/skills/checkpointing and .opencode/skills/checkpointing in your project.

What does Checkpointing need to run?

Going by SKILL.md and its folder, Checkpointing needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Checkpointing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Checkpointing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Checkpointing use?

Checkpointing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Checkpointing use?

About 1.8k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Checkpointing?

Skills that share tags, products or a category with Checkpointing: Strategic Compact (affaan-m/ECC, 277k stars), Progressive Jpeg (thedaviddias/Front-End-Checklist, 74k stars), Rebuilding Flutter Tool (flutter/flutter, 180k stars) and Modeling Activation Metrics (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Checkpointing?

DeL-TaiseiOzaki (a GitHub user) maintains it in DeL-TaiseiOzaki/claude-code-orchestra, which has 199 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 20, 2026.

Source: DeL-TaiseiOzaki/claude-code-orchestra on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.